Capital Budgeting Decision Making through Monte Carlo Simulation

This assignment discusses the variations of possibilities regarding the Net Present Value (NPV) of a project. The distribution model shows that the mean value of NPV will be calculated and relevant standard deviation applied to account for the level of risk taken in the project. Monte Carlo Simulation allows managers to see the continuum of all possible results rather than just getting a single estimate, enabling them to consider uncertainties explicitly involved in capital budgeting projects.

Running head: CORPORATE FINANCIAL MANAGEMENT
Corporate Financial Management
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Introduction
Uncertainty hovers over every project when it is started and determination of risks is
key for making decisions which is required by the managers. Big companies are known to
incorporate tough ways to tackle risks in case of capital budgeting (Gitman, Juchau and
Flanagan 2015). Therefore, every manager should know the methods of risk assessment. The
main jobs of corporate managers are to make profits for their company but they should also
know how to mitigate risks.
Capital budgeting related to sensitivity analysis
One of the several methods for identifying risks is sensitivity analysis which assists in
showing the alterations in NPV related to the applied change of a variable given as input on
the contrary when other things stay the same (Slagmulder, Bruggeman and Wassenhove
2013). Input variables are determined with their base value by the managers to conduct
sensitivity analysis. The base value is the most relevant value which is deemed to occur
predicted by the corporate manager.
When determination of base value is done then requirement of testing the net present
value of the sensitivity of the cash flow is there which is related to the variation in variable
concerned with some percentage of units that keeps other variables constant. It is important to
note that the change in values must be made keeping the relation of amount of products sold
and cost in mind (Burns and Walker 2015). It can be argued that, sensitivity analysis is the
key in showcasing the effect of changes which occur in taking assumptions. It must be
mentioned that sensitivity analysis supports decision making for various capital budgeting. It
also helps the managers to notice how the possible NPV are distributed and the impact
perceived by the internal return rate of the project which is under discussion. It also oversees

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the influence in a specific input variable. At any given time, managers taking the decisions
are needed to create assumptions regarding the project in a way that time taken, amount of
sales units in the project and the capital cost is considered.
Corporate managers need to know about the authenticity of the assumptions and the
expected changes in the final outcome of the project so that they cannot make incorrect
assumptions (Fama 2014). The process of measurement of sensitivity of the outcomes taking
part in the speculations for the project is known as Sensitivity analysis. In this, alteration of
one speculation is done to keep others intact which will determine the changes which will
occur in NPC and IRR. Cash flows are being foretold by the managers at the time of capital
budgeting.
Sales forecast and the cost are the fundamentals on which other systems of cash flow
forecasting is done. Sales volume and selling price of a unit is reflected by the sales revenue.
Market shares of the organization and size of the market depends of the sales volume of the
concerned project. Analysis of the tax cash flow done by the concerned managers determines
the IRR and NPV (Grob 2013). This is computed by adding different variables of discount,
cash flows, rate and project life. Hence it can be said that each variable is uncertain in most
cases. Variables which are set for the project are sensitive and their degree if sensitivity is
determined by doing sensitivity analysis. Therefore, the sensitivity of IRR and NPV is
determined by the analysis about alterations in a specific variable.
Capital budgeting related to Scenario analysis
As depicted in scenario analysis, one variable is changes at appoint of time. Since all
variables are correlated, as they must be to be relevant in all cases when each scenario
portrays different combination of variables. Scenario analysis is termed as the approach of
behaviour and is same as sensitivity analysis but has a wider perspective (Brunzell, Liljeblom

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and Vaihekoski 2013). It calculates the effect which a change in organization brings when the
numbers of variables are changed such as capital cost, cash inflow and outflow. For example,
the company may determine the low and high values of the NPV of the concerned project.
Individual scenario assists in showing the various stages of NPV with variables such as cash
inflow, capital cost and cash outflow.
NPV estimates can be used by the managers with the prospect of risk evaluation
related to the project concerned with the degree of inflation. During decision making process,
the managers are unsure of their assumptions. Some of those assumptions can alter the course
of problems and its specifics (Hartman 2014). It is known facts that sensitivity analysis is the
most popular technique of capital budgeting but it come with some limitations. But these
uncertainties are resolved through scenario analysis. It incorporates the possibilities with the
respective variables and provides the managers with a chance to change numerous variables
at one time.
Most certain set of variables taken as input variables make the base method of
Scenario analysis. Then it moves towards the worst case scenario slowly and then jumps to
the best case scenario (Fama 2013). It must be mentioned that there are some daring
managers who get carried away with the most certain results and ignore the possibilities some
vague assumptions can create which may be fluctuations in the economy and uncertain
reactions of the competitors. All the possible outcomes can be taken into account through
Scenario analysis including best case and worst case scenarios.
There are four important points to be considered in the analysis. In the primary stages,
determination of factors which will be foundations for assuming scenarios is done. These
factors may be the economic condition and the competitor’s reaction on any business activity
of the company (Titman and Martin 2014). The second factor consists of establishing various

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scenarios which needs to be analysed by keeping each factor under consideration. In usual
practice, there are three basic factors the first one is the best case scenario, second one is
average case scenario and the last one is the worst case consequence. The third factor is
considered by focusing on important factors and establishing specific consequence for every
factor (Baños-Caballero, García-Teruel and Martínez-Solano 2014). Each factor is given a
certain probability which will make the final component. The macro-economic factors such
as rate of interest, rate of exchange and factors of micro economics and reactions of the
competitors compute to make the assignments. Analysis of each and every scenario is done at
the time of preparing NPV.
Capital budgeting related to Break Even analysis
Managers do the sensitivity analysis in which they come against the problem about
the status of the project when the sales will decrease or the cost will increase. Production
quantity and the minimum rate of sale are to be known by the managers in any case so that
the project does not incur loss (Higgins 2012). This phenomenon is called break-even-
analysis and the least quantity which needs to be produced to evade loss is the break-even-
point. In terms of capital budgeting the project which is at the break-even is as good as the
business which givers zero percent return.
An individual or a company both get their return of the actual investment in the above
mentioned scenario. But the factor of time value of money is not compensated and there is no
reimbursement of the value of risk which was taken by the investor. If seen in different
context, managers tend to let go of their cost of opportunity of capital invested. Hence, it can
be stated that the project which breaks even accords negative NPV (Brealey, Allen and
Mohanty 2012). Breakeven analysis is a better place to start but it ignores some of the most
important information. It is oblivious to the matters of possibilities of acquiring proper results

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or how the outcome will result into. It can be seen by managers as a big winning opportunity
by ignoring the possibility of losing some money. Therefore it can be said that Break-even
analysis stresses more on NPV and ignores the aspects of profits made by accounting.
Capital budgeting related to Simulation analysis
Analysis done of the scenario and the sensitivity are known to be the best models for
knowing the uncertainties of investment in the projects. Hence it can be noted here that both
the above mentioned models do not consider the relationship between the variables and
ignores the possibilities of alterations in the variables (Aebi, Sabato and Schmid 2012). There
is method called Monte Carlo Simulation Analysis which helps the computer in adding the
risks involved in capital budgeting.
The name Monte Carlo is given because the method which contains numbers, driven
randomly from the distribution possibilities. It is known to be statistics based method that
applies numbers which are random and previously given possibilities which can change the
result of the entire project and its gains (Brigham and Houston 2012). It requires high end
functionality of the computer to work in efficient manner. Analysis done for simulation is
varied from the basic concept of sensitivity analysis in ways that differ from estimation of
important variables, probable distribution of values for every variable is applied.
The process of simulation structure generation starts from the computer that calculates
simultaneous values in a random manner for every known variable which might be same as
the model of project life, market, sale price, growth rate and cost of the variable etc. In the
guidance of set of values which are randomly selected a new order of cash flow is generated
and fresh NPV is calculated (Wang and Sarkis 2013). The same method is applied on
different places which can go to few hundred times or even greater than that if the project is

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huge. The managers are equipped with this procedure to make project decisions on the
variations of possibilities regarding the NPV of the project.
Distribution model shows that the mean value of NPV will be calculated and the
relevant standard deviation will be applied the take account of the level of risk taken in the
project (Brigham and Ehrhardt 2013). When the possible outcomes are distributed, then the
manager gets the chance of seeing the continuum of all possible results rather than just
getting a single estimate. It is imperative to note here that Monte Carlo Simulation includes
the possibilities and the sensitivities coming in distribution. The most important aspect of this
structure is that it allows the managers and stakeholders to take note of the possibilities of
NPV distributions in place of a single estimate of the concerned NPV (Arnold 2013).
Strength of simulation analysis makes its impact on the differences as it properly tackles all
the problems of many exogenous entities involved in any kind of distribution. It forces the
managers to consider the indecisions and uncertainties explicitly that are involved in the
projects of capital budgeting.
Conclusion
The above mentioned discussion emphasis on methods used in capital budgeting
which are mainly rooted on the speculations and uncertainty. All the decisions of investments
made by the managers are going to be constructed on the establishment of various important
matters which includes market value of the company, cash flow generated by the company
and dividends paid.
Methods used in capital budgeting gives the managers the options as they are
equipped with accurate details which are compiled with much precaution and carefulness so
that if they are used then they should not create problems when the circumstances change

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which may be of economic or technological nature. In those circumstances the evidences
produced by the computer can be of much help and can save the day for the managers.

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Reference
Aebi, V., Sabato, G. and Schmid, M., 2012. Risk management, corporate governance, and
bank performance in the financial crisis. Journal of Banking & Finance, 36(12), pp.3213-
3226.
Arnold, G., 2013. Corporate financial management. Pearson Higher Ed.
Baños-Caballero, S., García-Teruel, P.J. and Martínez-Solano, P., 2014. Working capital
management, corporate performance, and financial constraints. Journal of Business
Research, 67(3), pp.332-338.
Bodie, Z., 2013. Investments. McGraw-Hill.
Brealey, R.A., Myers, S.C., Allen, F. and Mohanty, P., 2012. Principles of corporate finance.
Tata McGraw-Hill Education.
Brigham, E.F. and Ehrhardt, M.C., 2013. Financial management: Theory & practice.
Cengage Learning.
Brigham, E.F. and Houston, J.F., 2012. Fundamentals of financial management. Cengage
Learning.
Brunzell, T., Liljeblom, E. and Vaihekoski, M., 2013. Determinants of capital budgeting
methods and hurdle rates in Nordic firms. Accounting & Finance, 53(1), pp.85-110.
Burns, R. and Walker, J., 2015. Capital budgeting surveys: the future is now.
Fama, E.F., 2013. Risk-adjusted discount rates and capital budgeting under
uncertainty. Journal of Financial Economics, 5(1), pp.3-24.

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Gitman, L.J., Juchau, R. and Flanagan, J., 2015. Principles of managerial finance. Pearson
Higher Education AU.
Grob, H.L., 2013. Capital budgeting with financial plans: an introduction. Springer-Verlag.
Hartman, J.C., 2014. The parallel replacement problem with demand and capital budgeting
constraints. Naval Research Logistics (NRL), 47(1), pp.40-56.
Higgins, R.C., 2012. Analysis for financial management. McGraw-Hill/Irwin.
Slagmulder, R., Bruggeman, W. and van Wassenhove, L., 2013. An empirical study of capital
budgeting practices for strategic investments in CIM technologies. International journal of
production economics, 40(2-3), pp.121-152.
Titman, S. and Martin, J.D., 2014. Valuation. Pearson Higher Ed.
Wang, Z. and Sarkis, J., 2013. Investigating the relationship of sustainable supply chain
management with corporate financial performance. International Journal of Productivity and
Performance Management, 62(8), pp.871-888.